Optimal warehouse location and size under risk of failure

Oshan, Tareq; Caron, Richard J.

doi:10.1080/23302674.2023.2208276

Cited by 4 publications

(1 citation statement)

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“…The cornerstone of every supply-chain system is the strategic placement of facilities that cater to the demand nodes by delivering goods and services. Research conducted by Caron and Oshan [1,9] underscores the pivotal role of facility-location optimization in enhancing both the profitability and resilience of businesses. Their studies not only demonstrated the practical efficacy of optimization models in real-world contexts, but also addressed the critical issue of potential facility failures.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Warehouse Location and Fortification: A Mixed-Integer Nonlinear Modeling Approach

Oshan

2024

Preprint

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This study presents a mathematical model for optimizing warehouse-location decisions in supply-chain network design. Previous studies have modeled the facility-location problem and provided fortification plans and solutions. However, these studies did not consider multi-capacity warehouses. The proposed model identifies optimal warehouse locations, sizes, and branch-warehouse assignments, and it determines fortification measures to mitigate the risk of warehouse failure. The model is formulated as a mixed-integer nonlinear problem and is subsequently linearized using standard linearization techniques combined with a proposed method based on the average-probability approximation. A case study of a Canadian company is used to illustrate the model's efficacy. Sensitivity analysis results demonstrate that when the numbers of fortified and built warehouses are equal, failure probability has no effect on the objective function of the model. Thus, this study presents a comprehensive model that can be used to assist businesses in decision-making regarding their warehouse operations to lower their risk of failure and optimize their use of warehouse infrastructure.

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Section: Introductionmentioning

confidence: 99%